Linking Visual Phenotypes with Genotypes in Plants - Content Management, Knowledge Sharing, and Database Retrievals

密苏里-哥伦比亚大学授予Chi-Ren Shyu博士早期职业发展资助，以开发视觉表型知识联盟的新方法，这些方法可以在当今多样化，不断变化和不一致的数据库，模式和术语中发挥作用和蓬勃发展。该项目中提出的知识共享中心能够使用不同的计算资源来可靠地交换数据和计算，而用户很少干预。第二个挑战是开发回答研究人员混合查询的方法，这些方法是科学专业知识和算法的组合，这些算法检测和检索与图像特征，语义描述，地图位置和DNA序列模式相关的信息，即使这些数据目前在合作伙伴的数据库中彼此不相关。拟议的混合查询系统将是研究界第一个也是唯一一个允许研究人员或教育工作者向数据库提交突变体图像并询问"是什么基因或环境因素导致这种视觉表型？“该项目包括两个独特方面的教育部分：一个重点是培训本科生和研究生，并为他们创建与研究活动密切相关的课程。新课程名为“生物信息学中的内容管理”和“生物信息学中的计算机视觉和图像理解”，将成为计算生物学课程设计的先驱课程。另一个重点将利用拟议的研究活动，结合传统的计算机科学课件，为计算和生物教育创建科学数据库。

The University of Missouri-Columbia is awarded an early career development grant for Dr. Chi-Ren Shyu to develop new approaches to knowledge federation of visual phenotypes that can function and flourish in today's landscape of diverse, constantly changing and inconsistent databases, schema, and terminology. The knowledge-sharing hub proposed in the project has the ability to use disparate computational resources to reliably exchange data and computations with little intervention from the user. A second challenge is to develop methods that answer the researchers' hybrid queries, which are combinations of scientific expertise and algorithms that detect and retrieve information related by image features, semantic description, map location, and patterns of DNA sequences, even when those data are not currently correlated with each other in the partner's databases. The proposed hybrid query system will be the first and only in the research community that allows a researcher or an educator to submit an image of a mutant to the database and ask, "What genes or environmental factors cause this visual phenotype?" The [roject includes an educational component with two unique aspects: One focus is on training of undergraduate and graduate students and creating courses for them that are closely aligned with the research activities. The new courses, titled "Content Management in Bioinformatics," and "Computer Vision and Image Understanding in Bioinformatics" will be pioneering courses in computational biology curriculum design. The other focus will leverage the proposed research activities to create, in conjunction with traditional computer science courseware, scientific data repositories for computation and biology education.